Asynchronous transfer mode (ATM) communications infrastructure has become widely deployed in the core of most telecommunications carrier's networks. Over time a greater variety of communications services and a growing volume of traffic is moving over these ATM networks. The commercial end users—businesses and institutions—are relying more and more on these ATM networks to support and implement their business critical systems.
Although ATM technology was specifically designed to allow the networks to provide a high level of service quality and reliability, ATM like all other networking technologies is subject to certain types of degradation and failure. Following a practice that is well established in time division multiplexing and in frame relay, commercial end users of ATM networks are demanding specific, contractually enforceable guaranties of performance quality from the network operators. These guaranties often take the form of service level agreements (SLA).
In order for the network operators to better report compliance to the SLA, telecom equipment manufacturers, often through participation in working groups within standards bodies, have sought to define methods for measuring several key SLA components. The performance of an ATM network can be measured by evaluating four parameters: availability ratio (AR), cell loss ratio (CLR), cell transfer delay (CTD) and cell delay variance (CDV).
Determination of AR and availability has typically used the measurement of severely errored seconds (SES) as the basis for evaluating availability. Measurement of SES occurs at the data link layer of an ATM network. As such, methods based on SES are dependent on the level of user traffic for accuracy and require a high level of computing intensity at each measurement point. In addition, the solutions recommended have, in some cases, applied to a limited set of connection types.
Efforts have been made to determine availability at higher levels in a network, such as the transport layer. A typical implementation includes the insertion of hardware based probes in-line with the connections to be monitored. These solutions often also include the injection of signaling message cells into the user data streams on the connections. The relatively high cost and complexity of probe deployment together with the impact of augmenting user data traffic has proved to be objectionable. Further, such solutions do not provide the ability to offer bi-directional availability measurements.